
Detailed information 
Original study plan 
Master's programme Mechatronics 2022W 
Objectives 
The students have acquired a sound understanding of the foundations of granular mechanics for both systems with and without interstitial fluid phase. They know several models for such systems and know which one is the most appropriate under given conditions. This involves
 microscopic,
 mesoscopic and
 macroscopic
models.
Furthermore, the students are familiar with various numerical methods to use these models in computer simulations. They know their algorithmic properties regarding
 stability,
 accuracy and
 efficiency
as well as important aspects for the implementation of these techniques.
The level of the mathematical treatment corresponds roughly to that of the textbooks (i) Rao, Nott: An Introduction to Granular Flow. Cambridge University Press, 2008, (ii) Ferzinger, Peric: Computational Methods for Fluid Dynamics. Springer, 2002 and (iii) Pöschel, Schwager: Computational Granular Dynamics. Springer, 2005.

Subject 
Introduction to the physical concepts of particleladen flows:
 NavierStokes equations for the continuous phase
 Newton‘s law of motion for macroscopic particles and their mutual interaction
 Combined description of particlefluid systems at various scales
Different models and algorithms for the simulations of granular systems and particleladen flows:
 Discrete element method (DEM), e.g. using the velocityVerlet algorithm
 Computational fluid dynamics coupled with discrete elements (CFDDEM), e.g. using the PISO algorithm
 Twofluid model (TFM)

Criteria for evaluation 
Written or oral exam; homework exercises

Methods 
Lecture, lecture notes

Language 
English 
Study material 
Rao, Nott: An Introduction to Granular Flow. Cambridge University Press, 2008 Johnson: Contact Mechanics. Cambridge University Press, 1985 Ferzinger, Peric: Computational Methods for Fluid Dynamics. Springer, 2002 Pöschel, Schwager: Computational Granular Dynamics. Springer, 2005

Changing subject? 
No 
Further information 
Until term 2022S known as: 481WTMKEPSK13 KV Introduction to particle simulation

